-
Notifications
You must be signed in to change notification settings - Fork 31
/
Copy pathcmq_rate_swap.py
178 lines (160 loc) · 8.29 KB
/
cmq_rate_swap.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
from QuantLib import *
import copy
import os
import json
from cmq_inst import CMQInstrument
import cmq_utils
import cmq_curve
import cmq_cashflow
import cmq_rate_index
def calibrate_ycurve(market_data, field='IRYCurve_usd3m'):
today = Date(str(market_data['MarketDate']), "YYYY-MM-DD")
Settings.instance().evaluationDate = today
quotes = market_data[field]
calib_helpers = []
calendar = cmq_utils.Calendar.US_UK
dayroll = cmq_utils.DayRoll.ModifiedFollowing
daycount = cmq_utils.DayCount.ACT360
for quote in quotes:
inst_name, inst_tenor = quote[0].split('_')
if inst_name == "CD":
ratehelper = DepositRateHelper(QuoteHandle(SimpleQuote(float(quote[1]))), \
cmq_utils.Period(str(inst_tenor)), 2,
calendar, dayroll, False, daycount)
elif inst_name == "IRF":
ratehelper = FuturesRateHelper(QuoteHandle(SimpleQuote(100 - float(quote[1]) * 100)),
cmq_utils.Date(str(inst_tenor)), 3,
calendar, dayroll, True, daycount,
QuoteHandle(SimpleQuote(0.0)))
elif inst_name == "IRS":
ratehelper = SwapRateHelper(QuoteHandle(SimpleQuote(float(quote[1]))),
cmq_utils.Period(str(inst_tenor)), calendar,
Semiannual, cmq_utils.DayRoll.Unadjusted,
cmq_utils.DayCount._30360US, USDLibor(Period(3, Months)))
else:
raise NameError('The instrument name %s is not supported' % inst_name)
calib_helpers.append(ratehelper)
# libor_fac = cmq_rate_index.LiborIndexFactory('3M', calendar, daycount)
spotdate = today
yield_curve = PiecewiseFlatForward(spotdate, calib_helpers, daycount)
return yield_curve
class CMQRateSwap(CMQInstrument):
def __init__(self, trade_data, market_data):
super(CMQRateSwap, self).__init__(trade_data, market_data)
def set_market_data(self, market_data):
cmq_utils.Date.set_origin(*[int(s) for s in market_data['MarketDate'].split('-')][::-1])
super(CMQRateSwap, self).set_market_data(market_data)
self.index_curve = calibrate_ycurve(market_data, 'IRYCurve_usd3m')
self.disc_curve = self.index_curve
def set_trade_data(self, trade_data):
self.calendar = cmq_utils.Calendar.US_UK
self.fix_freq = '6M'
self.flt_freq = '3M'
self.flt_daycount = cmq_utils.DayCount.ACT360
self.fix_daycount = cmq_utils.DayCount._30360US
margin = trade_data.get('Margin', 0.0)
lev = trade_data.get('Leverage', 1.0)
notional = trade_data.get('Notional', 1e6)
strike = trade_data['Strike']
start_date = cmq_utils.str2tenor(trade_data.get('StartDate', None))
end_date = cmq_utils.str2tenor(trade_data.get('EndDate', None))
tenor = cmq_utils.Period("%sM" % (int((end_date - start_date) / 365.0 * 12)))
libor_fac = cmq_rate_index.LiborIndexFactory(self.flt_freq, self.calendar, self.flt_daycount)
flt_fac = cmq_cashflow.LegFactory(self.flt_freq, self.calendar, self.flt_daycount, libor_fac,
notl_base=notional,
rate_spread=margin,
rate_leverage=lev)
fix_fac = cmq_cashflow.LegFactory(self.fix_freq, self.calendar, self.fix_daycount,
index_fac=cmq_rate_index.FixedIndexFactory(strike))
swap_fac = cmq_cashflow.InterestRateSwapFactory(rleg_fac=flt_fac, pleg_fac=fix_fac)
self.swap = swap_fac.create(start=start_date, tenor=tenor)
def clean_price(self):
disc = cmq_curve.DiscountCurve(0, self.index_curve.discount)
return self.swap.value(disc, disc, disc)
class CMQIRSwap(CMQInstrument):
def __init__(self, trade_data, market_data):
self.index = None
self.swap_engine = None
super(CMQIRSwap, self).__init__(trade_data, market_data)
def set_market_data(self, market_data):
cmq_utils.Date.set_origin(*[int(s) for s in market_data['MarketDate'].split('-')][::-1])
super(CMQIRSwap, self).set_market_data(market_data)
ycurve = calibrate_ycurve(market_data, 'IRYCurve_usd3m')
self.index_curve = RelinkableYieldTermStructureHandle()
self.index_curve.linkTo(ycurve)
self.swap_engine = DiscountingSwapEngine(self.index_curve)
self.disc_curve = self.index_curve
def set_trade_data(self, trade_data):
super(CMQIRSwap, self).set_trade_data(trade_data)
calendar = UnitedStates()
fix_tenor = Period(6, Months)
fix_adj = Unadjusted
fix_daycount = Thirty360()
self.index = USDLibor(Period(3, Months), self.index_curve)
flt_tenor = Period(3, Months)
flt_adj = ModifiedFollowing
flt_daycount = self.index.dayCounter()
margin = trade_data.get('Margin', 0.0)
notional = trade_data.get('Notional', 1000000)
strike = trade_data['Strike']
start_date = cmq_utils.str2tenor(trade_data.get('StartDate', None))
end_date = cmq_utils.str2tenor(trade_data.get('EndDate', None))
stype_in = trade_data.get("SwapType", "Payer")
if stype_in == "Payer":
swapType = VanillaSwap.Payer
else:
swapType = VanillaSwap.Receiver
fix_schd = Schedule(start_date, end_date,
fix_tenor, calendar,
fix_adj, fix_adj,
DateGeneration.Backward, False)
flt_schd = Schedule(start_date, end_date,
flt_tenor, calendar,
flt_adj, flt_adj,
DateGeneration.Backward, False)
self.swap = VanillaSwap(swapType, notional,
fix_schd, strike, fix_daycount,
flt_schd, self.index, margin,
flt_daycount)
def price(self):
self.set_trade_data(self.trade_data)
self.swap.setPricingEngine(self.swap_engine)
return self.swap.NPV()
class CMQIRBermSwaption(CMQIRSwap):
def __init__(self, trade_data, market_data):
self.exercise_dates = []
self.swaption = None
self.swap = None
super(CMQIRBermSwaption, self).__init__(trade_data, market_data)
def set_market_data(self, market_data):
super(CMQIRBermSwaption, self).set_market_data(market_data)
def calibrate_swnvol(self, market_data):
today = Settings.instance().evaluationDate
calendar = UnitedStates()
spotdate = calendar.advance(today, Period(2, Days))
swnvols = market_data["SWNVOL_usd3m"]
swn_tenors = [ten for ten, quote in swnvols]
swn_quote = [quote for ten, quote in swnvols]
berm_dates = [calendar.advance(spotdate, Period(ten[0], Months)) for ten in swn_tenors]
exercise = BermudanExercise(berm_dates[:-1], False)
self.swaption = Swaption(self.swap, exercise)
self.exercise_dates = berm_dates[:-1]
helpers = [SwaptionHelper(Period(ten[0], Months), Period(ten[1], Months), \
QuoteHandle(SimpleQuote(vol)), self.index, \
self.index.tenor(), self.index.dayCounter(), \
self.index.dayCounter(), self.index_curve) for ten, vol in swnvols]
sigmas = [QuoteHandle(SimpleQuote(0.01))] * (len(self.exercise_dates) + 1)
reversion = [QuoteHandle(SimpleQuote(0.01))]
gsr = Gsr(self.index_curve, self.exercise_dates, sigmas, reversion, 20.0)
swaption_engine = Gaussian1dSwaptionEngine(gsr, 64, 7.0, True, False, self.disc_curve)
for h in helpers:
h.setPricingEngine(swaption_engine)
method = LevenbergMarquardt()
ec = EndCriteria(1000, 10, 1E-8, 1E-8, 1E-8)
gsr.calibrateVolatilitiesIterative(helpers, method, ec)
self.swaption.setPricingEngine(swaption_engine)
def set_trade_data(self, trade_data):
super(CMQIRBermSwaption, self).set_trade_data(trade_data)
def price(self):
self.calibrate_swnvol(self.market_data, self.trade_data)
return self.swaption.NPV()